Statistical Optimization of the Content Composition Precursors Using Response Surface Methodology to Enhance Agaricoglyceride A Production from the Shaggy Ink Cap Medicinal Mushroom, Coprinus comatus (Higher Basidiomycetes) Mycelia

摘要

Coprinus comatus, a novel cultivated edible mushroom, has a various of pharmacological effects due to its many active components. In this study, agaricoglycerides, a new class of fungal secondary metabolites that have strong activity against neurolysin, were isolated from C. comatus mycelia. Simultaneously, a 3-level Box-Behnken factorial design was used, combined with response surface methodology, to optimize the precursor composition of agaricoglycerides for the production of agaricoglyceride A. The model estimated that a maximal yield of agaricoglyceride A (20.105 mg/L) could be obtained when the concentrations of 4-hydroxybenzoic acid, glycerol, and methanol (MeOH) were set at 75 mg/L, 0.75 mL/L, and 0.75 mL/L, respectively. The verified experiments showed that the model was significantly consistent with the model prediction. These results showed that appropriately adding the precursors could increase the production of agaricoglyceride A.